Neuron Primer Optogenetics in Neural Systems Ofer Yizhar, 1 Lief E. Fenno, 1 Thomas J. Davidson, 1 Murtaza Mogri, 1 and Karl Deisseroth 1,2,3,4, * 1 Department of Bioengineering 2 Department of Psychiatry and Behavioral Sciences 3 CNC Program 4 Howard Hughes Medical Institute Stanford University, Stanford, CA, 94305, USA *Correspondence: [email protected]DOI 10.1016/j.neuron.2011.06.004 Both observational and perturbational technologies are essential for advancing the understanding of brain function and dysfunction. But while observational techniques have greatly advanced in the last century, tech- niques for perturbation that are matched to the speed and heterogeneity of neural systems have lagged behind. The technology of optogenetics represents a step toward addressing this disparity. Reliable and targetable single-component tools (which encompass both light sensation and effector function within a single protein) have enabled versatile new classes of investigation in the study of neural systems. Here we provide a primer on the application of optogenetics in neuroscience, focusing on the single-component tools and highlighting important problems, challenges, and technical considerations. Introduction Optogenetics, as the term has come to be commonly used, refers to the integration of optics and genetics to achieve gain- or loss-of-function of well-defined events within specific cells of living tissue (Deisseroth et al., 2006; Scanziani and Ha ¨ usser, 2009; Deisseroth 2010, 2011). For example, microbial opsin genes can be introduced to achieve optical control of defined action potential patterns in specific targeted neuronal popula- tions within freely moving mammals or other intact-system prep- arations. Interdisciplinary by nature, optogenetics requires (1) engineered control tools that can be readily targeted to specific cells, (2) technologies for light delivery, and (3) methods for inte- grating optical control with compatible readouts (such as fluores- cent organic or genetically encoded activity indicators, electrical recording, fMRI signals, or quantitative behavioral analysis). Aspects of the conceptual inspiration for optogenetics can be traced to the 1970s. In 1979 Francis Crick, taking note of the complexity of the mammalian brain and the fact that electrodes cannot readily distinguish different cell types (Crick, 1979), sug- gested that a major challenge facing neuroscience was the need to precisely control activity in one cell type while leaving the others unaltered. Crick later speculated in lectures that light might be a relevant control tool, but without a concept for how this could be done. Yet years earlier (in an initially unrelated line of research), bacteriorhodopsin had been identified (Oesterhelt and Stoecke- nius, 1971, 1973) as a microbial single-component light-activated ion pump. Further work in thousands of papers over the ensuing decades led not only to deeper understanding of bacteriorho- dopsin but also to the discovery of many new members of this microbial opsin family, which includes membrane-bound ion pumps and channels such as halorhodopsins (Matsuno-Yagi and Mukohata, 1977) and channelrhodopsins (Nagel et al., 2002) that transport various ions across the membrane in response to light (Matsuno-Yagi and Mukohata, 1977; Lanyi and Oesterhelt, 1982; Schobert and Lanyi, 1982; Be ´ ja ` et al., 2000; Nagel et al., 2002, 2003; Ritter et al., 2008; Zhang et al., 2008). It took decades for these two concepts to be brought together by neuroscientists, although microbial opsin genes were widely known and had long been understood to give rise to single-component light-activated regulators of trans- membrane ion conductance. But there were fundamental caveats for those who considered such a possibility for optical neural control over the decades, including the presumption that photocurrents would be too weak and slow to control neurons efficiently, the presumption that microbial membrane proteins in fragile mammalian neurons would be poorly expressed or toxic, and most importantly the presumption that additional cofactors such as all-trans retinal (the separate organic light- absorbing chromophore employed by microbial opsins) would have to be added to any intact-tissue experimental system. These preconceptions (strikingly similar to those that slowed the development of green fluorescent protein) were all reason- able enough to deter experimental implementation, and efforts were therefore focused elsewhere. Yet in the summer of 2005 it was reported that introduction of a single-component microbial opsin gene into mammalian neurons (without any previously tested or other component) resulted in reliable sustained control of millisecond-precision action potentials (Boyden et al., 2005); many additional papers from work conducted contemporaneously appeared over the next year (Li et al., 2005; Nagel et al., 2005; Bi et al., 2006; Ishizuka et al., 2006). Moreover, while retinoids were already well known to be present in large quantities in embryonic tissues and in the retina, it was soon found that mature mammalian brains (Dei- sseroth et al., 2006; Zhang et al., 2006), and indeed all verte- brate tissues thus far examined (e.g., Douglass et al., 2008) contain sufficient all-trans retinal for microbial opsin genes to define a single-component strategy. By 2010 the major classes of ion-conducting microbial opsins (including bacteriorho- dopsin, channelrhodopsin, and halorhodopsin) had all proven to function as optogenetic control tools in mammalian neurons, as described below. Neuron 71, July 14, 2011 ª2011 Elsevier Inc. 9
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Neuron
Primer
Optogenetics in Neural Systems
Ofer Yizhar,1 Lief E. Fenno,1 Thomas J. Davidson,1 Murtaza Mogri,1 and Karl Deisseroth1,2,3,4,*1Department of Bioengineering2Department of Psychiatry and Behavioral Sciences3CNC Program4Howard Hughes Medical InstituteStanford University, Stanford, CA, 94305, USA*Correspondence: [email protected] 10.1016/j.neuron.2011.06.004
Both observational and perturbational technologies are essential for advancing the understanding of brainfunction and dysfunction. But while observational techniques have greatly advanced in the last century, tech-niques for perturbation that are matched to the speed and heterogeneity of neural systems have laggedbehind. The technology of optogenetics represents a step toward addressing this disparity. Reliable andtargetable single-component tools (which encompass both light sensation and effector function withina single protein) have enabled versatile new classes of investigation in the study of neural systems. Herewe provide a primer on the application of optogenetics in neuroscience, focusing on the single-componenttools and highlighting important problems, challenges, and technical considerations.
IntroductionOptogenetics, as the term has come to be commonly used,
refers to the integration of optics and genetics to achieve gain-
or loss-of-function of well-defined events within specific cells
of living tissue (Deisseroth et al., 2006; Scanziani and Hausser,
2009; Deisseroth 2010, 2011). For example, microbial opsin
genes can be introduced to achieve optical control of defined
action potential patterns in specific targeted neuronal popula-
tions within freely movingmammals or other intact-system prep-
arations. Interdisciplinary by nature, optogenetics requires (1)
engineered control tools that can be readily targeted to specific
cells, (2) technologies for light delivery, and (3) methods for inte-
grating optical control with compatible readouts (such as fluores-
cent organic or genetically encoded activity indicators, electrical
recording, fMRI signals, or quantitative behavioral analysis).
Aspects of the conceptual inspiration for optogenetics can be
traced to the 1970s. In 1979 Francis Crick, taking note of the
complexity of the mammalian brain and the fact that electrodes
cannot readily distinguish different cell types (Crick, 1979), sug-
gested that a major challenge facing neuroscience was the need
toprecisely control activity in one cell typewhile leaving theothers
unaltered. Crick later speculated in lectures that light might be a
relevant control tool, but without a concept for how this could
be done. Yet years earlier (in an initially unrelated line of research),
bacteriorhodopsin had been identified (Oesterhelt and Stoecke-
nius, 1971, 1973) as amicrobial single-component light-activated
ion pump. Further work in thousands of papers over the ensuing
decades led not only to deeper understanding of bacteriorho-
dopsin but also to the discovery of many new members of this
microbial opsin family, which includes membrane-bound ion
pumps and channels such as halorhodopsins (Matsuno-Yagi
and Mukohata, 1977) and channelrhodopsins (Nagel et al.,
2002) that transport various ions across the membrane in
response to light (Matsuno-Yagi and Mukohata, 1977; Lanyi and
Oesterhelt, 1982; Schobert and Lanyi, 1982; Beja et al., 2000;
Nagel et al., 2002, 2003; Ritter et al., 2008; Zhang et al., 2008).
It took decades for these two concepts to be brought
together by neuroscientists, although microbial opsin genes
were widely known and had long been understood to give
rise to single-component light-activated regulators of trans-
membrane ion conductance. But there were fundamental
caveats for those who considered such a possibility for optical
neural control over the decades, including the presumption that
photocurrents would be too weak and slow to control neurons
efficiently, the presumption that microbial membrane proteins
in fragile mammalian neurons would be poorly expressed or
toxic, and most importantly the presumption that additional
cofactors such as all-trans retinal (the separate organic light-
absorbing chromophore employed by microbial opsins) would
have to be added to any intact-tissue experimental system.
These preconceptions (strikingly similar to those that slowed
the development of green fluorescent protein) were all reason-
able enough to deter experimental implementation, and efforts
were therefore focused elsewhere. Yet in the summer of 2005 it
was reported that introduction of a single-component microbial
opsin gene into mammalian neurons (without any previously
tested or other component) resulted in reliable sustained
control of millisecond-precision action potentials (Boyden
et al., 2005); many additional papers from work conducted
contemporaneously appeared over the next year (Li et al.,
2005; Nagel et al., 2005; Bi et al., 2006; Ishizuka et al., 2006).
Moreover, while retinoids were already well known to be
present in large quantities in embryonic tissues and in the
retina, it was soon found that mature mammalian brains (Dei-
sseroth et al., 2006; Zhang et al., 2006), and indeed all verte-
brate tissues thus far examined (e.g., Douglass et al., 2008)
contain sufficient all-trans retinal for microbial opsin genes to
define a single-component strategy. By 2010 the major classes
of ion-conducting microbial opsins (including bacteriorho-
dopsin, channelrhodopsin, and halorhodopsin) had all proven
to function as optogenetic control tools in mammalian neurons,
Since earlier, multicomponent efforts for photosensitization of
cells (for example, involving cascades of multiple genes or
combinations of genes and custom organic chemicals (Zemel-
man et al., 2002, 2003; Banghart et al., 2004; Lima and Miesen-
bock, 2005; Kramer et al., 2005; Volgraf et al., 2006) have been
recently reviewed (Gorostiza and Isacoff, 2008; Miesenbock,
2009), here we provide a primer focusing on single-component
optogenetics, delineating guiding principles for scientific investi-
gation and summarizing the enabling technologies for neurosci-
ence application. However, most of the techniques developed
for this approach (ranging from genetic targetingmethods, to ad-
dressing experimental confounds, to intact-system light delivery
methods) will be relevant to any biological system or optogenetic
strategy. We do not attempt to review in any form the very large
number of papers and results that have emerged in this field,
nor to address every technique, reagent, and device linked to
optogenetics. Rather, here we highlight limitations, challenges,
and obstacles in the field and outline general principles for
designing, conducting, and reporting optogenetic experiments.
Microbial Opsin GenesOptogenetics is not simply photoexcitation or photoinhibition
of targeted cells; rather, optogenetics must deliver gain or loss
of function of precise events—just as in genetics, where
single-gene manipulations are the core currency of the field.
This means that in neuroscience, millisecond-scale precision is
essential to true optogenetics, to keep pace with the known
dynamics of the targeted neural events such as action potentials
and synaptic currents. Moreover, this level of precision must
be operative within intact systems including freely moving
mammals. All strategies to achieve optical control, including
those involving microbial opsin genes, initially displayed serious
limitations in meeting this goal. The multicomponent character,
longer-timescale temporal properties, and/or requirement for
high-intensity UV light characteristic of the earlier strategies
(Zemelman et al., 2002; Banghart et al., 2004; Lima and Miesen-
bock, 2005; Kramer et al., 2005) have limited adoption and appli-
cation to mammalian and other systems, but single-component
microbial opsin gene strategies also initially displayed problems
as well ranging from inadequate control capability (Boyden et al.,
2005; Gunaydin et al., 2010) to toxicity (Gradinaru et al., 2008,
2010; Zhao et al., 2008) to challenges linked to light delivery
in vivo (Aravanis et al., 2007; Adamantidis et al., 2007). A long
process of tool engineering and substantial development of
enabling technologies was required over the next several years.
The key properties of these microbial optogenetic tools relate
to the ecology of their original host organisms, which respond to
the environment using seven-transmembrane proteins encoded
by the type I class of opsin gene (Yizhar et al., 2011b). Type I
opsins are protein products of microbial opsin genes and are
termed rhodopsins when bound to retinal. However, in typical
heterologous expression experiments the precise composition
of retinoid-bound states is uncharacterized. Therefore in the
setting of neuroscience application, the tools are conservatively
referred to as opsins (amore accurate and convenient shorthand
for common use, since only ‘‘opsin’’ correctly applies to the
genes as well as to the protein products). These proteins are
distinguished from their mammalian (type II) counterparts, in
10 Neuron 71, July 14, 2011 ª2011 Elsevier Inc.
that they are single-component light-sensing systems; the two
operations—light sensing and ion conductance—are carried
out by the same protein.
The first identified, and still by far the best studied, type I
protein is the haloarchaeal proton pump bacteriorhodopsin
(BR; Figure 1A; Oesterhelt and Stoeckenius, 1971, 1973; Racker
and Stoeckenius, 1974). Under low-oxygen conditions, BR is
highly expressed in haloarchaeal membranes and serves as
part of an alternative energy-production system, pumping
protons from the cytoplasm to the extracellular medium to
generate a proton-motive force to drive ATP synthesis (Racker
and Stoeckenius, 1974; Michel and Oesterhelt, 1976). These
light-gated proton pumps have since also been found in a wide
range of marine proteobacteria as well as in other kingdoms of
life, where they employ similar photocycles (Beja et al., 2001;
Varo et al., 2003) and have been hypothesized to play diverse
roles in cellular physiology (Fuhrman et al., 2008).
A second class of microbial opsin genes encodes halorhodop-
sins (Figure 1A). Halorhodopsin (HR) is a light-activated chloride
pump first discovered in archaebacteria (Matsuno-Yagi and
Mukohata, 1977). The operating principles of halorhodopsin
(HR) are similar to those of BR (Essen, 2002), with the two
main differences being that halorhodopsin pumps chloride ions
and its direction of transport is from the extracellular to the intra-
cellular space. Specific amino acid residues have been shown to
underlie the differences between BR and HR in directionality and
preferred cargo ion (Sasaki et al., 1995). After initial identification
of halorhodopsin, other members of this class soon followed;
for example, Lanyi and colleagues expanded the family by iden-
tifying a halorhodopsin from Natronomonas pharaonis in 1982
(NpHR; Lanyi and Oesterhelt, 1982).
Next, a third class of conductance-regulating microbial opsin
gene (channelrhodopsin or ChR) was identified (Figure 1A).
Nagel and Hegemann demonstrated light-activated ion-flux
properties (Nagel et al., 2002) for a protein encoded by one of
the genomic sequences from the green algae Chlamydomonas
reinhardtii, as Stoeckenius, Oesterhelt, Matsuno-Yagi, and
Mukohata had earlier for the proteins halorhodopsin and
bacteriorhodopsin. Subsequent papers from several groups
described a second and third channelrhodopsin (Nagel et al.,
2003; Zhang et al., 2008), and many more will follow. While
ChR is highly homologous to BR, especially within the trans-
membrane helices that constitute the retinal-binding pocket,
in channelrhodopsins the ion-conducting activity is largely un-
coupled from the photocycle (Feldbauer et al., 2009); an effective
cation channel pore is opened, which implies that ion flux
becomes independent of retinal isomerization and rather
depends on the kinetics of channel closure. In neurons, net
photocurrent due to ChR activation is dominated by cation
flow down the electrochemical gradient (resulting in depolariza-
tion), rather than by the pumping of protons. Like the BRs
and HRs, ChRs from various species (Nagel et al., 2002; Zhang
et al., 2008) are functional in neurons with a range of distinct
and useful intrinsic properties.
The single-component optogenetic palette available to neuro-
scientists now contains tools for four major categories of fast
excitation, fast inhibition, bistable modulation, and control of
intracellular biochemical signaling in neurons and other cell
ChR2C128A
ChR2C128T
ChR2C128S
ChR2D156A
ChR2D156A/C128S
VChR1
Hyperpolarizing
C1V1E122T/E162T
VChR1C123S
VChR1C123S/D151A
NpHR
Arch eBR
1 ms 10 ms
400
450
500
550
600
650
100 ms 1 s 10 s 100 s 1000 s 10000 s
E123A
E123T ChIEF
L132C*T159C
ChRGR*
WTE123T/T159C
H134R
Opto- 2Opto- 1Rh-CT
bPACBlaC
C1V1
C1V1E162T
Peak
Act
ivat
ion
(n
m)
o
Step Function Opsin (bistable depolarization)
Fast Excitation
Fast Inhibition
Biochemical modulation
1 min 30 min
A
B
Na+
Na+ Na+
Na+
Na+
Na+
K+
H+
H+
H+
H+H+
H+
K+K+K+
K+
K+
Na+
Na+Na+ Na+ Ca2+
Ca2+
Ca2+
Na+
Na+
ChR
Red-shifted depolarizing
Bistable depolarizing
ChETA variants
Blue depolarizing
Biochemical modulation
Cl-
Cl-
Cl
Cl
-
Cl-
Cl-
-
Cl-
Cl-
Cl-
Cl-
Cl-
Cl-
Cl-
Cl-
Cl-Cl-
HR
H+
H+
H+
H+
+
H+
H
H+
H+
H+
H+
H+
H+H+
H+
H+
BR / PR
[IP3][DAG] [cAMP] [cAMP]
GqGs Gi
OptoXR
ATPATP
cAMP
BacterialCyclase
Figure 1. Basic Properties of Known Single-Component Optogenetic Tools with Published Spectral and Kinetic Information(A) Single-component optogenetic tool families; transported ions and signaling pathways are indicated.(B) Kinetic and spectral attributes of optogenetic tool variants for which both of these properties have been reported and for which minimal activity in the dark isobserved. Visible spectrum shown; not venturing into the ultraviolet is preferred, for safety and light penetration reasons, although the 450–470 nm peak probesalso can be excited very effectively with UV light (�360–390 nm). Decay kinetics are plotted against peak activation wavelength only to demonstrate groupingsand classes over the range of spectral and temporal characteristics and the feasibility of dual channel control using tools that are well separated in the spectraland temporal domains; see Table 1 for additional information and references. Kinetic data are not published for the proton pump Mac but the Mac actionspectrum peak �565 nm is identical to that of Arch (Chow et al., 2010). Opto-XR kinetics were obtained in vivo and should be taken only as an upper boundsince the assay involved a downstream measure (spiking). Decay kinetics are temperature dependent; all other reported values except ChRGR are recorded atRT, with �50% decrease in toff expected at 37C. *Since ChRGR has only been studied at elevated (34�C) T, we denote likely RT range for ChRGR shifted to theright. Values for channelrhodopsin/fast receiver and channelrhodopsin/wide receiver (Wang et al., 2009) can be estimated at 7 and 14 ms, respectively; these arenot shown but respond at 470 nm and have not yet been functionally validated in neurons. L132C (CatCH) toff value was not measured in neurons, and itsproperties may depend on other channels in the host cell as well as the host cell tolerance of, and response to, higher levels of elevated intracellular Ca2+
(Kleinlogel et al., 2011).
Neuron
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types (Figure 1B, Table 1). This array of optogenetic tools, the
result of molecular engineering and genomic efforts, allows
experimental manipulations tuned for (1) the desired physiologic
effect; (2) the desired kinetic properties of the light-dependent
modulation; and (3) the required wavelength, power, and spatial
extent of the light signal to be deployed.
Fast Optogenetic Excitation for Neuroscience
Microbial opsin genes in some cases lead to expression of light-
inducible photocurrents when introduced into neurons, but to
date, optogenetic application of all of these genes has benefited
substantially from molecular modification. In neuroscience, after
initial demonstration (Boyden et al., 2005; Li et al., 2005; Nagel
et al., 2005; Bi et al., 2006; Ishizuka et al., 2006), a subsequent
widely used form of channelrhodopsin was generated by
substituting mammalian codons to replace algal codons in
order to achieve higher expression levels (humanized ChR2 or
hChR2; Zhang et al., 2006; Adamantidis et al., 2007; Aravanis
et al., 2007; Zhang et al., 2007), and this process is now typically
applied to all new opsin genes. An important caveat is that
codon optimization and mutagenesis can lead to unanticipated
effects in different experimental systems, and an intervention
that gives rise to improved properties in mammalian neurons
(such as point mutation, codon optimization or membrane
trafficking modification) could in principle show impairment in
other properties (and unchanged or even impaired performance
in another cell or system). For example, introduction of the
H134R mutation into ChR2 was found to be of mixed impact,
improving currents �2-fold during prolonged stimulation
Neuron 71, July 14, 2011 ª2011 Elsevier Inc. 11
Table 1. Single-Component Optogenetic Tools with Both Spectral and Kinetic Data Published
Opsin Mechanism Peak Activation l Off Kinetics (t, ms)* Kinetics References
Blue/Green Fast Excitatory
ChR2 Cation channel 470 nm �10 ms Boyden et al., 2005;
Nagel et al., 2003
ChR2(H134R) Cation channel 470 nm 18 ms Nagel et al., 2005;
Gradinaru et al., 2007
ChR2 (T159C) Cation channel 470 nm 26 ms Berndt et al., 2011
GFAP) have been characterized (Brenner et al., 1994) that can
drive specific expression of transgenes in astrocytes (excluding
neurons) both with VSVG-pseudotyped LV (Jakobsson et al.,
2003) and with AAV (serotypes 8 and rh43; Lawlor et al., 2009);
these have now been applied for optogenetic experiments
(Gradinaru et al., 2009; Gourine et al., 2010) using the low Ca2+
flux through the ChR channel to trigger Ca2+ waves and activate
astroglial signaling. The human Synapsin I (Nathanson et al.,
2009b; Diester et al., 2011) and human Thy1 (Diester et al.,
Neuron 71, July 14, 2011 ª2011 Elsevier Inc. 17
Injection Site
LocalSomata
CombinatorialLocal Somata
Viral Expression Light Delivery
Opsin expression throughout B Illumination of B cell bodiesprojecting to A and C
Single viral injection into B
Virallyencodedopsin
A
BC A
BC A
BC
Laser
Opsin expression in B cell bodiesaccording to viral promoters or
recombinase-dependent expresion
Mixed viral injection with spectrally-separated opsins into
mixed population of neurons in B
Mixture ofvirally encodedopsins
A
BC A
BC A
BC
Laser 1
Laser 2
Precisely temporally separableillumination of mixed neuronal
populations in B with two colors of light
A
Projection
Illumination of B axonsin A but not C. Corresponding
cell bodies in B may be activated.
Single viral injection into B
Virallyencodedopsin
A
BC A
BC A
BC
Laser
Opsin expression throughout B
C
CombinatorialProjection
F
ProjectionTermination
Virally encodedlectin-recombinase
fusion
Opsin expression in B neuronsthat project to A (also achievable
with axon-transducing viruses)
Illumination of B cell bodiesor B axons in A withoutdirect modulation of C
Double viral injection into B and A.Recombinase expressed in A moves
transcellularly to cells in B.
Virally encodedrecombinase-dependent opsin
A
BC A
BC A
BC
Laseror
LaserD
Recombinase- or promoter-dependent
Opsin expression only in neuronsexpressing recombinase orwith active promoter in B
Illumination of B cell bodies andmodulation of recombinase- or
promoter-expressing cells
Single viral injection intomixed population of neurons in B
Virally encodedrecombinase- or promoter-dependent opsin
A
BC A
BC A
BC
LaserB
E
Opsin expression in A and C cellbodies according to viral promoters
or recombinase activity
Illumination of mixed neuronalprojections in B activate independent
axons from A and C
Viral injection of spectrally separated opsins into A and C
Independentvirally-encodedopsins
A
BC A
BC A
BC
Laser 1
Laser 2
Opsin expression throughout B Illumination of B cell bodiesprojecting to A and C
Single viral injection into B
Virallyencoded
yy
opsinA
BC A
BC A
BC
Laser
Opsin expression in B cell bodiesaccording to viral promoters or
recombinase-dependent expresion
Mixed viral injection with spectrally-separated opsins into
mixed population of neurons in B
Mixture ofvirally encodedopsins
y
A
BC A
BC A
BC
Laser 1
Laser 2
Precisely temporally separableillumination of mixed neuronal
populations in B with two colors of lig
Illumination of B axonsin A but not C. Corresponding
cell bodies in B may be activated.
Single viral injection into B
Virallyencoded
yy
opsin
A
BC A
BC A
BC
Laser
Opsin expression throughout B
ncodedbinasefusion
Opsin expression in B neuronsthat project to A (also achievable
with axon-transducing viruses)
Illumination of B cell bodiesor B axons in A withoutdirect modulation of C
Double viral injection into B and A.Recombinase expressed in A moves
transcellularly to cells in B.
Virally encodedrecombinas
ye-
dependent opsinA
BC A
BC A
BC
Laseror
Laser
Opsin expression only in neuronsexpressing recombinase orwith active promoter in B
Illumination of B cell bodies andmodulation of recombinase- or
promoter-expressing cells
Single viral injection intomixed population of neurons in B
Virally encodedrecombinas
ye- or promoter-
dependent opsinp
A
BC A
BC A
BC
Laser
Independentvirally
p-encoded
opsinsy
A
BC A
BC A
BC
Laser 1
Laser 2
Figure 2. Targeting Optogenetic Tools In Vivo(A) Direct stimulation of neuronal cell bodies is achieved by injecting virus at the target region and then implanting a light-delivery device above the injected region.Even this simple experiment can provide specificity with viruses that will not transduce afferent axons and fibers of passage.(B) Additional cell-type specificity is attained either by cell-type-specific promoters in the viral vector or via a recombinase-dependent virus, injected ina transgenic animal expressing a recombinase such as Cre in specific cells, leading to specific expression of the transgene only in defined cell types.(C) Projection (axonal) targeting is achieved by viral injection at the region harboring cell bodies, followed by implantation of a light-delivery device above thetarget region containing neuronal processes from the virally transduced region; in this way cell types are targeted by virtue of their projections.(D) Projection termination labeling is a more refined version of projection targeting, in which cells are targeted by virtue of synaptic connectivity to the targetregion and likely excluding cells with axons simply passing through the region. Transcellular labeling using a recombinase-dependent system is shown. Virusesexpressing Cre fused to a transneuronal tracer (lectin) are delivered at the synaptic target site, and a Cre-dependent virus is injected into the region with cellbodies. Cells that project to the Cre-injected area express the Cre-dependent virus and become light sensitive. This can also be achieved with axon terminal-transducing viruses although without control over the postsynaptic cell type.
18 Neuron 71, July 14, 2011 ª2011 Elsevier Inc.
Neuron
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Neuron
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2011) promoters can be used to selectively target opsins to
neurons (excluding glia) in a range of systems from rodent to
primate (see Table 2).
It remains a major challenge to identify neuron-type-specific
promoter fragments small enough to be packaged into viral
payloads, certainly in primate tissues but also in rodents and
other experimental systems. Several inhibitory neuron-specific
promoters have been characterized, although these are not
specific to subsets of inhibitory cells (Nathanson et al., 2009a;
Table 2). For broad excitatory neuron targeting, the Ca2+/
calmodulin-dependent kinase II alpha (CaMKIIa) promoter has
been shown to express mainly in excitatory neurons in cortex
and hippocampus (Dittgen et al., 2004), and for many years
has been applied for optogenetic control in a range of systems
(Aravanis et al., 2007; Zhang et al., 2007; Han et al., 2009; Sohal
et al., 2009; Johansen et al., 2010; Lee et al., 2010). Finally, in
certain systems, specific virus-compatible promoters for hypo-
cretin neurons, serotonin neurons, and somatostatinergic
neurons have been described (Adamantidis et al., 2007; Tan
et al., 2008; Benzekhroufa et al., 2009a, 2009b; Tan et al.,
2010; Table 2). An important caveat, however, is that promoter
specificity observed in one region of organism may not hold in
other tissues or organisms, and promoter and tropism strategies
are not truly generalizable. Additionally, promoter specificity
must be accompanied by viral access: a given neuron must
both express the viral receptor and the promoter in order to be
specified in this manner. Where available, each promoter must
be characterized for cell-type specificity within the context of
the chosen viral vector, organism, and brain region.
For simple optogenetic applications with small promoters,
such as the expression of an opsin gene tagged with a fluores-
cent protein, AAV vectors are sufficient. However, expression
of larger genes and larger promoters, or coexpression of more
than one optogenetic tool, requires careful consideration when
choosing the appropriate vector. The main challenge in
achieving specific expression with viral targeting is that the
genome size contained in a viral capsid is limited, depending
on the virus type and serotype. For example, LV particles can
carry a genome of up to 9 kb (Kumar et al., 2001), including the
regulatory elements and viral genes encoded within. AAV-based
vectors are generally restricted to a genome size of 4.7 kb,
although new methods might facilitate expression of larger
genomes (Dong et al., 1996, 2010). For expression of even larger
genomes (e.g., with larger promoter fragments or transgenes),
adenoviral vectors can carry up to 27 kb of geneticmaterial (Sou-
dais et al., 2004). Herpes simplex-based vectors (HSV; Lilley
et al., 2001; Lima et al., 2009; Covington et al., 2010; Lobo
et al., 2010) also have greater carrying capacity and offer the
potential for transducing axon terminals more efficiently than
LV or most AAV serotypes, although consistency and toxicity
are concerns for HSV approaches (Fink et al., 1996). This
axonal-transduction property (shared with rabies viruses, pseu-
dotyped LVs, some AAVs, and pseudorabies viruses (Kaspar
et al., 2002; Burger et al., 2004; Kato et al., 2007; Callaway,
(E) Expression of two opsins with different characteristics in one brain region usisomata is performed using two different wavelengths designed to minimize cros(F) Projections from two different brain regions are differentially stimulated with t
2008; Miyamichi et al., 2011; Kato et al., 2011) can be either
a feature or a bug in a given optogenetic experimental paradigm.
This property when utilized diminishes one of the valuable spec-
ificities of virus-based optogenetics, which has been confine-
ment of opsin gene transduction to local cell bodies without
the confound of transducing (and photosensitizing) incoming
afferents (e.g., Lee et al., 2010). On the positive side, such ‘‘retro-
grade’’ transduction provides one means for targeting neurons
based on connectivity (although other methods described below
exist to achieve this goal).
As noted above, relying on idiosyncratic known viral tropisms
or finding suitable virus-borne promoter fragments is not
currently available for optogenetic control of most neuronal
subtypes. However, the strategy of designing viruses that can
leverage the large and rapidly growing armamentarium of animal
lines that express exogenous recombinases only in defined cell
types (driver lines, which can fully capitalize on enormous native
promoter/enhancer regions rather than the small fragments
which fit into viruses) offers an expanded range of opsin targeting
strategies (Figure 2B; see Table 3 for driver lines used in optoge-
netic studies). New driver lines are continually added to the avail-
able repertoire by groups such asGENSAT and the Allen Institute
for Brain Science. Successfully utilizing a recombinase driver line
requires efficient packaging of the genetic material to be ex-
pressed into a recombinase-dependent system conferring the
two properties of (1) very low leak (background) of opsin expres-
sion in non-recombinase-expressing cells, and (2) very high re-
combinase-induced opsin expression—all within the viral back-
bone.
Several potential different recombinase-dependent viral
vector designs have emerged (Kuhlman and Huang, 2008;
Zhang, 2008; Atasoy et al., 2008; Sohal et al., 2009), and a Cre
recombinase-dependent double-floxed inverted opsin gene in
AAV under the EF1a promoter (Zhang, 2008; Sohal et al., 2009)
or the CAG promoter (Atasoy et al., 2008) was ultimately found
to provide a suitable combination of strength and specificity to
enable behaviorally significant optogenetic gain or loss of func-
tion within the constraints of the freely moving mammal system
(Tsai et al., 2009; Aponte et al., 2011). Not only is this strategy
versatile in the sense that it can be applied at will to the large
and growing pool of Cre driver lines (e.g., Gong et al., 2007),
soon to include rat as well as mouse lines, but this approach is
also by design expandable along new dimensions that enable
combinatorial experiments (Figure 2). First, other recombinases
such as Flp or Dre may be used to construct orthogonal driver
lines that can be crossed with Cre driver lines while the same
low-leak, high-potency recombinase-dependent AAV design is
theoretically adaptable for these other recombinases as well.
Second, promoter fragments may be used at the same time in
place of the EF1a promoter in the recombinase-dependent
viruses, thereby implementing intersecting promoter and recom-
binase-dependent specificity. Third, while generation of recom-
binase-dependent opsin mouse lines for simply crossing with
Cre driver lines is a viable approach (Madisen et al., 2010a,
ng a combination of promoter or Cre-based approaches. Light delivery to thes-activation.wo wavelengths matched to the respective opsins expressed upstream.
Neuron 71, July 14, 2011 ª2011 Elsevier Inc. 19
Table 3. Cre Driver Mouse Lines Successfully Employed for Biological Findings in Optogenetic Studies
Mouse Line Expression In Vector Used Use References
and animal behavior. In utero electroporation (IUE) may be
employed to target opsins to distinct layers of the cortex, capital-
izing on the sequential layer-by-layer ontogeny of neocortex in
mammals, by incorporating the DNA into neurons generated
during a specific embryonic stage (Petreanu et al., 2007, 2009;
Huber et al., 2008; Adesnik and Scanziani, 2010). Beyond this
special targeting capability, an additional unique advantage of
22 Neuron 71, July 14, 2011 ª2011 Elsevier Inc.
IUE is that opsins are expressed from before the time of litter
birth (allowing electrophysiological experiments at a younger
stage than with viral expression).
Optogenetic tools have been well tolerated when electropo-
rated into mouse embryos in naked plasmid form. In principle,
cells may also be targeted for optogenetic control by (1) active
proliferation status at a particular moment in time, using cell-
cycle-dependent Moloney-type retroviruses (Toni et al., 2008);
(2) location at a particular moment in time (e.g., via migration
through a particular anatomical location during development;
and (3) othermethods including ex vivo sorting followed by trans-
duction and transplantation. In general, the range of genetic
techniques for delivering opsin genes into the brain has become
broad and versatile and leverages the intrinsic tractability of the
single-component microbial opsin tools.
Associated Enabling Technologies for Optogeneticsin Neuroscience: Light DeliveryOnce the desired opsins have been targeted to neurons of
interest, the next experimental consideration is light delivery.
Requirements vary widely across experimental paradigms. For
instance, amultiple-opsin study of fast oscillations in a brain slice
preparation will require a different light delivery approach than
a study of the effects of prolonged stimulation of a deep brain
nucleus in a behaving animal. Next we review strategies for
meeting the light requirements for particular experimental
applications via the spatial, temporal, and spectral control of
illumination.
Light Requirements for Activation at the Molecular
and Cellular Level
The photocurrent in a neuron resulting from a pulse of light will
depend upon many factors, including the properties of the opsin
being expressed, the wavelength, intensity and duration of
the incident light, and even recent illumination history (if fewer
channelrhodopsin molecules begin in or have returned to the
dark-adapted state, the initial transient response to a light pulse
will be smaller, though the steady-state photocurrent may remain
the same; Boyden et al., 2005; Rickgauer and Tank, 2009). In all
cases, however, the rate of absorption of photons of a given
wavelength is proportional to the local photon flux; that is, the
number of photons incident per unit time per unit area. When
designing a light delivery system to activate rhodopsins, it is
therefore chiefly this parameter that we wish to measure and
control.
Given the ease of measuring total light power (in Watts) using
commercially available light power meters, it is more convenient
to measure and report ‘‘light power density’’ (typically measured
in mW/mm2), rather than photon flux. Light power density is
simply the photon flux multiplied by the energy of the individual
photon, which is inversely proportional to wavelength. For
wild-type ChR2 at typical expression levels and illuminated
with 473 nm light, light power densities of �1–5 mW/mm2 were
initially found to be sufficient to elicit action potentials (Boyden
et al., 2005). Light requirements vary among different optoge-
netic tools, and one must consider the specific properties of
the opsin-retinal complex when designing the experiment. For
example, optogenetic inhibition may require continuous light
for as long as inhibition is desired, whereas bistable optogenetic
DA
E
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473 nm561 nm594 nm635 nm
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Figure 3. Light Propagation in Brain Tissuefor In Vivo Optogenetics(A) Schematic showing that the maximum activa-tion depth is the depth at which the light powerdensity falls below the activation threshold, PDmin.(B) Measured percent transmission of light powerat 473 nm, 561 nm, 594 nm, and 635 nm light froma fiberoptic (200 mm, NA = 0.37) shown as a func-tion of distance from the fiber tip in brain tissue.Solid lines represent fits to the measured data(Aravanis et al., 2007).(C) Predicted fraction of initial light power densityas a function of depth in brain tissue for the samefiber; includes effects of absorption, scattering,and geometric light spread.(D and E) Lateral light spread as a function ofsample thickness. Saline solution (top) or rat graymatter (bottom) was illuminated by either blue(473 nm; left) or yellow (594 nm; right) light deliv-ered through a 200 mm optical fiber (NA = 0.37).Images are sections through a 3D map of lightintensity along the axis of an illuminating fiber.Contour maps of the image data show iso-inten-sity lines at 50%, 10%, 5%, and 1% of maximum.Note conical spread of light in saline due to fiberproperties, and more symmetrical light propaga-tion shape in brain tissue.
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control (Berndt et al., 2009) only requires brief, widely spaced
light pulses, typically at much lower power (<0.01 mW/mm2).
We recommend that the light power density, rather than total
power, be reported in optogenetic studies. When illuminating
cultured cells with light coupled into a microscope’s beam path,
calculating light power density can be as simple as dividing the
total emitted light power by the area of the illuminated spot.
However, when shaped beams of light are directed into larger
volumes of tissue, such as with optical fiber illumination of
the intactbrain, estimating lightpowerdensityat the targeted loca-
tion requiresaccounting for attenuation introducedbybeamdiver-
genceand theoptical propertiesof the illuminated tissue (Aravanis
et al., 2007 and see below). Such calculations also help estimate
the volume of tissue recruited by the light stimulus in vivo and
are critical for the design and interpretation of experiments.
Optical Properties of Brain Tissue
For a given opsin gene, functional expression levels and the light
power density reaching the expressing cells will together deter-
mine the efficacy of light-based control (Figure 3A). To estimate
this density of light reaching the targeted cells onemust consider
the propagation of light in tissue. Light propagation in biological
tissue can be modeled as a combination of absorption and
scattering, with scattering playing an especially important role
in mature myelinated brain tissue (Vo-Dinh, 2003). The transmis-
sion properties of light through the brain also depend strongly on
wavelength, with longer-wavelength light scattering less and
therefore penetrating more deeply (Figure 3).
Neuro
We have taken several complementary
approaches to measuring and estimating
the depth of light propagation under
typical experimental conditions, specifi-
cally for the illumination of deep brain
structures using thin optical fibers. In
one approach (Aravanis et al., 2007), an
optical fiber emitting a known light power was lowered into
a block of unfixed brain tissue, and light power was measured
on the underside of the block, giving a transmission fraction for
the tissue sample (nontransmitted light was either absorbed by
or reflected out of the sample). This measurement was repeated
for a range of tissue thicknesses by stepping the fiber through
the block. These data were fit with standard equations for the
propagation of light in diffuse scattering media (Kubelka-Munk
model; Vo-Dinh, 2003), in order to estimate parameters that
could be used to predict depth of transmitted light power in other
experimental configurations.
To estimate the light power density at a given distance from
the fiber tip, the beam was modeled as spreading conically
within the tissue, with an angle determined by the optical prop-
erties of the fiber. This model, while involving a number of unre-
alistic assumptions including that the sample is a homogeneous,
ideal diffuser illuminated from one side with diffuse light, and
that reflection and absorption are constant over the thickness
of the sample, nevertheless allowed a good fit to measured
data (Figures 3B and 3C; Aravanis et al., 2007) when used to esti-
mate light power density at progressively deeper sites. Next, to
directly observe the lateral spatial extent of the illuminated region
at various distances from the fiber, we repeated the experiments
above with the block of brain tissue placed on a thin diffusing
layer revealing the two-dimensional pattern of illumination at
the bottom of the block; this screen was imaged from below
as the fiber was lowered through either brain tissue, or saline
n 71, July 14, 2011 ª2011 Elsevier Inc. 23
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solution, and the resulting images were stacked to create a
three-dimensional volume (Figures 3D and 3E). The light power
density profiles directly below the fiber were in general agree-
ment with the attenuation predicted by the simple conical model,
for distances corresponding to relative light power densities
down to 5% of the initial value. At greater distances, the higher
number of scattering events results in a higher degree of lateral
spread. A useful rule of thumb based on these direct measure-
ments (Figure 3E) is that the full (edge to edge) width of lateral
light spread, arising from an optical fiber in gray matter, is quan-
titatively similar to the full depth (fiber tip to edge) of forward light
spread at a given light level.
Thesedirectmeasurements provide the basis for a quantitative
estimation of the volume of tissue recruited during optogenetic
experiments, have been validated by light measurements and
electrophysiology at known distances from the illumination
source (Aravanis et al., 2007; Adamantidis et al., 2007; Gradinaru
et al., 2009; Cardin et al., 2009; Tye et al., 2011), and are gener-
ally consistent with immunohistochemical staining for molecular
markers of elevated activity such as c-fos (Gradinaru et al.,
2009). Complementing thesemeasurements, estimates of trans-
mission of light can be simulated with Monte-Carlo methods
(e.g., Bernstein et al., 2008), and as the geometry and chemical
composition of brain tissue are complex neither the simple
models nor the Monte Carlo simulations can be relied upon
without validation using direct measurements. Transmission
measurements and estimated light power densities for blue
(473 nm) and green (561 nm) light emitted from a fiberoptic
have been previously reported (Aravanis et al., 2007; Adamanti-
dis et al., 2007), but the advent of the new red-shifted optoge-
netic tools described above requires consideration of additional
wavelengths of light; here, we report these values for 473 nm,
561 nm, 594 nm, and 635 nm light in brain tissue (Figures 3B
and 3C). A simple calculator that estimates light power density
as a function of depth in tissue, using the data reported here
and allowing user input on wavelength, light power, and fiber
type, is available online at www.optogenetics.org/calc. This
depth estimation, when combinedwith the empirical observation
that the full (edge to edge) width of lateral light spread is quanti-
tatively similar to the depth of forward light spread from the fiber
tip for a given contour, allows rapid estimation of illumination
profiles for in vivo work. Spatial light targeting can bemultiplexed
with the opsin targeting strategies described above to further
restrict which components of the neural circuit are modulated.
Controls for Nonspecific Effects of Opsin Expression
and Light Delivery
The expression of exogenous opsins in tissue and the delivery of
the light needed to activate them may also result in unintended
effects, such as toxicity or tissue heating. Viral infection and
the expression of exogenous proteins at high levels could alter
cellular capacitance (Zimmermann et al., 2008), alter cellular
physiology, or even lead to toxicity; we and others have found
that the CMV, CAG, and rabies-based promoters may express
opsins at very high levels that can cause protein accumulations
or structural abnormalities in the targeted neurons over time.
However, very long-term expression of any membrane (or other
exogenous) protein with even more moderate-strength
promoters can cause toxicity, and we have found that expres-
24 Neuron 71, July 14, 2011 ª2011 Elsevier Inc.
sion strength and time of expression interact in giving rise to
this phenomenon.When employed, fusion proteins could appear
to mimic such an effect, but some fluorescent proteins such
as mCherry to which opsins are commonly fused themselves
can clump and accumulate, while not necessarily impairing
opsin function or cell health (e.g., Adamantidis et al., 2007).
Regardless, it is important to track membrane resistance and
resting potential; modest trends of effects on these membrane
properties are occasionally seen with high level opsin expres-
sion. Especially when such an effect is observed, it is important
to carry out no-light controls in opsin-expressing tissue or
animals.
Indeed, in theory not only intrinsic neuronal properties (such as
input resistance, membrane capacitance, and excitability) could
be altered by toxicity linked to long-term or very high-level
membrane protein overexpression, but even functional output
and effective synaptic connectivity could be altered. A no-light
control condition in which the tissue is virally transduced, but
no light is delivered, can address these effects and is especially
valuable when the light delivery paradigm does not involve
switching on-and-off and therefore within-animal controls are
less feasible (Tsai et al., 2009). For invertebrates such as
C. elegans and D. melanogaster, where retinal is not present
but may be easily supplied in food or substrate, another type
of control is possible, the retinal-negative condition (Zhang
et al., 2007).
Light used to activate opsins may also produce nonspecific
effects. Light leaking from the delivery apparatus, or scattered
through brain tissue may reach light-sensing organs such as
the retina, directly affecting neural activity, or leading to changes
in an animal’s behavior. Light absorbed by tissue could also
result in photodamage or local temperature increases. It is there-
fore critical that parallel no-opsin control experiments using
identical illumination conditions are included in optogenetic
experiments (e.g., Adamantidis et al., 2007; Tsai et al., 2009;
Lee et al., 2010).
The issue of tissue heating by light deserves special consider-
ation, since even temperature changes too small to cause
detectable tissue damage can lead to significant physiological
(Moser et al., 1993) and behavioral (Long and Fee, 2008) effects.
Consider pulsed laser light delivered to a deep brain region by
a thin optical fiber. Light is emitted in a conical pattern, then
scattered and absorbed as it passes through optically inhomo-
geneous brain tissue. Heat will be generated wherever light is
absorbed, in proportion to the light intensity at each point, giving
rise to a heat source that is distributed throughout the tissue. The
temperature gradient resulting from this heating will be counter-
acted over time by conduction of heat, bymass transfer (e.g., the
perfusion of the region by blood), and possibly also by changes
in metabolic heating as a result of stimulation or inhibition.
Notably, both scattering and absorbance vary with light wave-
length, with absorbance �10 times higher at 475 nm than
600 nm (Yaroslavsky et al., 2002). Therefore, even under condi-
tions of equivalent total light power delivery to the brain through
the same optical fiber, the spatial structure of the resulting heat
source can be markedly different for different wavelengths.
As an exercise it may be useful to estimate an upper bound
for temperature changes resulting at a targeted region under
Systems) in a number of useful wavelengths across the opsin
action spectrum with sufficient continuous-wave (CW) output
power; these include appropriate focusing optics and mounting
hardware and are compact, portable, and robust for daily lab
use. We have found that direct diode lasers tend to be more
reliably modulated at high speeds than DPSS lasers at similar
wavelengths. Lasers with a power output of �100 mW are typi-
cally used, driven with a power supply that allows for analog
modulation of output power. This level is sufficient to generate
high light power densities out of small optical fibers even after
coupling and transmission losses, after splitting into multiple
fibers, and after some degradation of output power with use.
Different wavelength outputs from DPSS lasers are achieved
by using different combinations of pump diodes and solid-state
gain media. Due to differences in the complexity, efficiency, and
tolerances of these devices, and in the control electronics they
require, DPSS lasers of the same power but different wavelength
can vary more than 10-fold in price and have very different
performance characteristics, especially with respect to temporal
modulation. For instance, 473 nm and 532 nm DPSS lasers can
reliably generate 1 ms pulses (though for pulses < 100 ms in
duration, the average power during a pulse may be significantly
less than the steady-state output at the same command voltage;
Figure 4B). On the other hand, 593.5 nm (yellow) DPSS lasers
cannot be reliably modulated even at the second timescale, so
we employ instead a high-speed shutter in the beam path
(Uniblitz, Stanford Research Systems, Thorlabs; Figure 4A).
High-speed beam shutters can be acoustically noisy (though
low-vibration shutters are manufactured by Stanford Research
Systems), and so experiments must be designed such that this
auditory stimulus time-locked to laser illumination does not
become confounding for intact animal preparations (even in
anesthetized preparations).
Neuron 71, July 14, 2011 ª2011 Elsevier Inc. 25
594 nmlaser
473 nmlaser
Photodetectors
AdjustableN.D. lter Shutter
SteeringMirror
Beampick-o
Dichroic(yellow-pass)mirror
Couplingoptics
Connector
Commutator
95%
5%95%
5%
Ferrule
Sleeve
FiberStub
B
A
C500 ms
5 mW
First
Last FirstLast
LaserOutputTrigger
1 ms5 mWLaser 1, TTL
First Last
LaserOutput
Trigger
Laser 1, Shutter
First Last
LaserOutput
Trigger
Laser 2, TTL
Figure 4. Two-Laser Setup for Optogenetic Stimulation(A) Two solid-state lasers are coupled into a single fiberoptic cable for two-color modulation. A fast laser shutter is used to control the output of the yellow(593.5 nm) laser, due to its slow analog modulation. Beam pick-offs allow foronline monitoring of laser output by photodetectors. An optical fibercommutator enables animals to freely move in the behavior apparatus withoutfiber twisting or breakage. A fiberoptic cable connects from the commutator toa fiberoptic implant consisting of a metal ferrule with a permanently attachedfiberoptic cable that extends into the target region.(B) Light power traces from three laser configurations generating 10 ms lightpulses at 10 Hz for 4 s. Top: A blue (473 nm) DPSS laser (e.g., OEM lasers)directly modulated using the laser’s TTL modulation mode. The upward powerdrift across the pulse train was repeatable. Middle: The same laser, with samecommand power, but in continuous operation, with modulation provided bya mechanical shutter (LS-2, Uniblitz) in the laser path. Bottom: A 488 nm directdiode laser (Phoxx, Omicron-Laserage).(C) Expanded view of the first and last pulses from (B). Note the ramping up ofpower and the reduced mean power output of the DPSS laser in response toa short pulse (top) as compared to the same laser’s steady state output(middle), and the �1 ms delay introduced by the shutter (middle).
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It is important to validate new equipment and all illumination
protocols using a high-speed photodetector (many commercial
power meters have an analog output that allows the raw light
power signal to be observed on an oscilloscope). Online
26 Neuron 71, July 14, 2011 ª2011 Elsevier Inc.
measurement of light power during experiments may also be
achieved by using a beam pickoff that directs a small fraction
of the modulated laser power to a photodetector continuously
during an experiment (Figure 4A).
LEDs
Light-emitting diodes (LEDs) are another attractive light source
for certain optogenetic applications. LEDs have the required
narrow spectral tuning (spectral linewidth at half maximum
typically in the 10 s of nm), are readily modulated at the frequen-
cies required, are simple and inexpensive, and do not require
complex control electronics; however, when used near tissue,
substantial heat is generated and caution is indicated for
in vivo use. Like lasers, only a limited number of colors are
available that emit adequate power, though increasing the power
output and spectral diversity of LEDs is an active area of
research. In vitro, LEDs can serve as the light source for optoge-
netic experiments (Ishizuka et al., 2006; Gradinaru et al., 2007;
Petreanu et al., 2007; Campagnola et al., 2008; Adesnik and
Scanziani, 2010; Grossman et al., 2010; Wen et al., 2010), and
LED arrays are available that permit focal stimulation of single
cells, or even single neurites (Grossman et al., 2010). For
in vivo applications, LEDs can be used to fill an optical fiber
which is tethered to a behaving animal, but such applications
are limited by the highly divergent beam pattern from LEDs
with coupling efficiencies of �1%; still, with high-power LEDs,
this fraction of total power is sufficient to attain the required
power density output (Gradinaru et al., 2007; Petreanu et al.,
2007). Possible uses of LEDs include both direct implantation
of small LEDs in or on tissue (with heating concerns requiring
careful control as noted above), or permanently mounted to
optical fiber waveguides carried on the subject (Iwai et al., 2011).
Incandescent Sources
Traditional broadband incandescent microscopy light sources,
such as arc lamp-based epifluorescence illuminators, can be
used in optogenetic experiments with appropriate narrowband
spectral filters and the introduction of a shutter to the illumination
beam path. Dedicated light sources with built-in high-speed
shutters and filter selection are also available (e.g., the Sutter
Instruments DG-4; Boyden et al., 2005) and offer pulse durations
of as little as 1 ms with pulse repetition rates of up to 500 Hz.
Unlike some lasers and LEDs, which offer graded modulation
of intensity, shutter-based systems are limited to on/off gating
of light pulses; neutral density filters can be used to produce
stepped illumination. One significant advantage of the use of
filtered broadband light over LEDs or lasers is the ability to select
arbitrary illumination wavelengths and spectral linewidth using
bandpass filters. Even more flexible are monochromators, which
output commanded wavelengths via positioning of a diffraction
grating.
Light Delivery: Surface Targets
In light-accessible experimental preparations such as cultured
neurons, brain slices, cortical surface, or nematodes, light is
typically delivered through a microscope illumination path,
passing through the objective and illuminating a spot within the
field of view. Apertures in the illumination path can be used to
restrict this spot to a smaller portion of the field. In order to
measure the light power density achieved by a given setup,
a power meter can be placed below the objective; the total
Figure 5. Implanted Fiberoptic Lightguide (IFL)The lightguide is composed of a fiberoptic cable terminated by a metal ferrule(1). The optic fiber can be cleaved to length based on stereotactic coordinates(2) and light can then be delivered by attaching a matched fiber-ferrule pairconnected to the output of the laser apparatus (3). Coupling of the fibers leadsto light propagation through the implant (4).
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power is measured and divided by the area of the illumination
spot (Aravanis et al., 2007). For experiments requiring illumina-
tion at multiple sites, or at sites away from the imaged area, an
optical fiber-coupled light source (see below) can be mounted
on a micromanipulator and used to illuminate the tissue, with
light power density similarly calculated from total power and
spot size. Laser beams can be coupled into the microscope light
path and optically expanded to fill the field of view, and moving
optical elements—such as galvanometer-driven mirrors (Rick-
gauer and Tank, 2009; Losonczy et al., 2010), digital micromir-
rors (Farah et al., 2007; Arrenberg et al., 2010), or diffractive
optical elements (Watson et al., 2009)—can be combined with
microscope optics to deliver patterns of light to areas within
the imaging field.
Indeed, spatiotemporal light patterning is a field of increasing
relevance to many aspects of optogenetics (Shoham, 2010).
Various methods of spatial and temporal beam shaping have
been explored for delivering complex two- or three-dimensional
patterns of light for single-photon (Farah et al., 2007) or two-
photon control of microbial opsin-derived tools (Rickgauer and
Tank, 2009; Andrasfalvy et al., 2010; Papagiakoumou et al.,
2010). It remains to be seenwhichwill be themost useful or prac-
tical method for controlling multiple cells in versatile and rapid
fashion within intact tissue, but already individual cells can be
controlled independently within living brain slices (Papagiakou-
mou et al., 2010) and freely moving worms (Leifer et al., 2011;
Stirman et al., 2011), opening up immense opportunities for
systems neuroscience.
Light Delivery: Deep Targets
Delivering light to in vivo preparations presents several distinct
challenges compared with in vitro preparations. Light may
need to be targeted to deep brain structures while minimizing
damage to surrounding tissue, and in the case of behaving
animals without significantly disrupting the behavior under
study. To satisfy these requirements, we developed the optical
neural interface discussed above for use in vivo that employs
a thin optical fiber to carry light from a source (typically a laser)
directly to the targeted structure (Adamantidis et al., 2007; Ara-
vanis et al., 2007). While above we discussed the propagation
of light after emerging from the fiber, here we address the fibers
themselves.
Fiberoptics are thin, flexible cables made of transparent
material that act as waveguides for light. The dimensions and
optical properties of a particular fiber will interact with other
elements in the light delivery system to affect the geometry
and intensity profile of the light beam delivered to the brain. In
conjunction with an understanding of the optical properties of
brain tissue addressed above, such variation can be exploited
in the targeting of light to particular regions (Adamantidis
et al., 2007; Aravanis et al., 2007). The light-carrying fiber either
can be inserted directly into the brain using a stereotaxic appa-
ratus (for anesthetized preparations) or can be inserted into a
cannula previously implanted stereotactically. Alternatively, a
short length of optical fiber with one end located at the targeted
brain region, and the other end terminated by a miniature
fiberoptic connector (Doric Lenses, Quebec, Canada), can be
permanently implanted and attached to the skull. This last
method (implanted fiberoptic lightguide or IFL; Figure 5) is
preferred for chronic experiments for a number of reasons; the
bare fiber causes less damage than the larger cannula, the brain
is completely closed to the outside environment, and mating the
connector is easier and potentially less disruptive than inserting
a fiber into a cannula.
The most common type of fiber, called step-index, consists of
a light-carrying ‘‘core’’ material (often silica glass) surrounded by
a thin ‘‘cladding’’ layer of material with a slightly higher refractive
index (often a hard transparent polymer). For light delivery, fiber
with a core diameter from the 10 s to 100 s ofmicrons and a clad-
ding thickness around 10 microns is typically chosen, with larger
core diameters providing for easier and more efficient coupling
of light into the fiber and a larger emitting area within the brain.
Fibers of these dimensions support many (typically thousands)
of discrete light propagation modes, and are therefore referred
to as ‘‘multimode’’ fiber. The core and cladding may be sur-
rounded by a protective ‘‘jacket’’ or ‘‘buffer’’ layer, which does
not contribute to light transmission and is stripped from the fiber
before insertion into the brain (Aravanis et al., 2007; Zhang et al.,
2010). The interface between the core and cladding reflects light
traveling through the core at angles close to the longitudinal axis
of the fiber (a phenomenon called ‘‘total internal reflection’’), with
the difference in refractive indexes between the core and clad-
ding determining the maximum angle of rays that can propagate
through the fiber. This relationship is captured by the fiber’s
numerical aperture (NA), which also determines the maximum
acceptance angle for incoming light and the maximum exit angle
for the output light beam. Fibers with an NA from 0.1 to 0.5 are
readily available, giving exit cone angles into brain tissue from
8 to 42 degrees. Since the attenuation with distance from the
fiber tip depends partly on the geometric spread of light, fiber
NA contributes to the shape of the tissue activated by a given
total emitted light power.
Laser light can be efficiently coupled into the fiber with an
optical part that focuses the incoming beam onto the end of
Neuron 71, July 14, 2011 ª2011 Elsevier Inc. 27
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the fiber. Couplers that attach directly to the laser head and
adjust using small screws are available, but we prefer to rigidly
attach the laser and coupler to an optical breadboard, and align
the beam using 2 adjustable steering mirrors (Figure 4), which
affords faster and more precise alignment. Moreover, this
arrangement allows for easy access to the beam path for intro-
ducing optical elements such as shutters, beam blocks, filters,
beam pick-offs, and power meters. Combining beams from
multiple lasers into a single fiber is also easily achieved by
the use of a dichroic mirror with the appropriate wavelength
cutoff.
Associated enabling technologies for optogeneticsin neuroscience: readoutsOptogenetic control has been shown to be compatible with
diverse behavioral readouts in organisms ranging from worms
and flies to fish and mammals, particularly since the fiberoptic
neural interfaces (Adamantidis et al., 2007; Aravanis et al.,
2007) are lightweight and flexible enough to allow complex
behaviors to be easily carried out in freely moving mammals.
One potential challenge to this approach could be a restriction
in movement arising from use of a fiber. Nevertheless, analogous
issues have been addressed and solved for electrical connec-
tors; in the case of optical hardware, optical commutators allow
tracks and arenas to be explored by fiberoptic-coupled
mammals exhibiting complex behaviors ranging from rapid
circling behavior to place preference and elevated plus maze
(Gradinaru et al., 2009; Witten et al., 2010; Tye et al., 2011).
Moreover, the latest generation of more light-sensitive and bista-
ble optogenetic tools may enable not only LED-based electrical
wire control during behavior, but also free behavior in the
complete absence of tethered optical devices (Berndt et al.,
2009; Yizhar et al., 2011a). Therefore, as behavioral measures
in the setting of optogenetics are relatively straightforward (Na-
gel et al., 2005; Adamantidis et al., 2007; Huber et al., 2008; Airan
et al., 2009; Tsai et al., 2009; Carter et al., 2009; Johansen et al.,
2010; Lobo et al., 2010; Witten et al., 2010; Tye et al., 2011) and
can be mapped onto the wide range of validated animal behav-
ioral measures present in the literature, here we do not focus on
behavioral measures, instead taking note of circuit-level read-
outs (electrical, optical, and magnetic resonance).
Electrical Readouts
A key advantage of optogenetic stimulation is that true simulta-
neous electrical recordings can be carried out. Such simulta-
neous input/output processing is not typically possible with
integrated electrical stimulation and electrical recording, due
to artifacts associated with electrical stimulation that have
stymied both basic systems neuroscience investigations and
our understanding of therapeutic brain stimulation modalities
such as DBS. Extracellular unit recordings are easily integrated
with light stimulation (Gradinaru et al., 2007, 2009), but local
field potential recordings with metal electrodes can be
confounded with electrical artifacts likely resulting from the
direct effects of light and temperature on the recording elec-
trode (Ayling et al., 2009; Cardin et al., 2010). Several simple
steps can be taken to assure that LFPs reflect neural activity,
including minimization of exposed metal area, use of glass elec-
trodes wherein the conducting wire can be placed further away
28 Neuron 71, July 14, 2011 ª2011 Elsevier Inc.
from the site of recording, and use of nichrome microwires
rather than tungsten microelectrodes. Control recordings
should be performed in brain regions that contain no opsin-ex-
pressing cells, with light at the same wavelength and power
density as those used in the experimental recordings within
the opsin-expressing region.
When light delivery and electrical recording are integrated into
a single device (Gradinaru et al., 2007), the resulting tool is
referred to as an ‘‘optrode’’ (Gradinaru et al., 2007, 2009; Zhang
et al., 2010). These have ranged from fusion of optical fibers with
metallic electrodes (Gradinaru et al., 2007, 2009), to coaxial inte-
gratedmultielectrode devices (Zhang et al., 2009a, 2009b; Royer
et al., 2010), to silicon probes for multi-site recording in awake,
behaving animals (Royer et al., 2010). An issue with all of these
extracellular methods is that there is no guarantee that recorded
spikes are arising from photosensitive cells, rather than from
indirectly recruited cells. Normally this is not a concern, and
optrode recordings still provide extremely useful feedback on
the activity in the local circuit during control that could never
be obtained with electrical stimulation. However, care must be
taken not to overinterpret (for example) latencies to spiking,
which can be highly variable in vivo due to differences in illumina-
tion intensity, as predictive of whether a unit is directly or indi-
rectly driven by light. Latencies as long as 10–12 ms or greater
are certainly possible for directly driven cells, while conversely
latencies as short as 3–4 ms should be possible even for indi-
rectly driven (nonphotosensitive) cells.
Optical Readouts
The concept of all-optical interrogation of neural circuits (Dei-
sseroth et al., 2006; Scanziani and Hausser, 2009) is appealing
since spatial distribution and cell-type information can be more
readily extracted from imaging data than from electrophysiology.
Dye-based imaging has been conducted in combination with
optogenetic control in a number of studies, using Ca2+ dyes
such as fura-2 (Zhang et al., 2007) and Fluo-5F (Zhang and Oert-
ner, 2007), and voltage-sensitive dyes such as RH-155 (Airan
et al., 2007, 2009; Zhang et al., 2010). The development of new
and improved genetically encoded sensors for neural activity
(Lundby et al., 2008; Dreosti et al., 2009; Dreosti and Lagnado,
2011; Lundby et al., 2010; Tian et al., 2009) opens up a new
class of possibilities for capitalizing on cell-type-specific readout
information that would complement the cell-type-specific play-in
of information provided by optogenetics. Although channelrho-
dopsin action spectra overlap to some extent with the excitation
spectra of these fluorophores, one canminimize photoactivation
during imaging by minimizing irradiance used to excite the
fluorophores, and by using scanning microscopy (confocal or
two-photon based).
When using scanning lasermicroscopy, the rapid ChR kinetics
that initially posed challenges for two-photon activation (Rickga-
uer and Tank, 2009) are actually favorable since Ca2+ imaging
can be performed by two-photon excitation with minimal photo-
activation of ChRs. Indeed, Zhang and Oertner used two-photon
imaging of the Ca2+ dye Fluo-5F to record dendritic calcium
transients evoked with either ChR2 photostimulation or direct
current injections in individual neurons in the slice culture
preparation (Zhang and Oertner, 2007), while Guo et al. used
GCaMP2 in C.elegans neurons, using a low wide-field light
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power density for imaging GCaMP (488 nm; 0.01 mW/mm2; Guo
et al., 2009) to avoid unwanted photostimulation by the
cocaine conditioning, and depression (Gradinaru et al., 2009;
Covington et al., 2010; Alilain et al., 2008; Kravitz et al., 2010;
Witten et al., 2010; Busskamp et al., 2010; Tye et al., 2011).
The temporal precision enabled by the use of light along with
the single-component microbial opsin strategy is crucial across
all fields for delivering a defined event in a defined cell population
at a specific time relative to environmental events. Moreover,
optogenetic tools may now be selected from a broad and ex-
panding palette (Figure 1) for specific electrical or biochemical
effector function, speed, action spectrum, and other properties.
Advances in tool functionality and targeting/readout enabling-
technologies have allowed the core goal of optogenetics in
neuroscience to be achieved: millisecond-scale optical control
of defined small-scale events occurring in specified cellular
populations while these populations remain embedded and
functioning within freely moving mammals or other intact and
complex biological systems.
ACKNOWLEDGMENTS
Tools and reagents are freely available at www.optogenetics.org and www.addgene.org, and hands-on optogenetics training courses are available(www.optogenetics.org). We gratefully acknowledge that this researchdirection was launched with funding beginning July 2004 to K.D. as principalinvestigator from the National Institutes of Health, from the Stanford Depart-ment of Psychiatry, and from the Stanford Department of Bioengineering(www.optogenetics.org/funding). Both this initial microbial opsin work andall subsequent work at Stanford over the years have been financially supportedwith grants awarded to K.D. from many generous agencies and donors,including from the National Institute of Mental Health, the NIH Director’sPioneer Award, the National Institute on Drug Abuse, the National Institute ofNeurological Disorders and Stroke, the National Science Foundation, theMichael J Fox Foundation, the Defense Advanced Research Projects Agency,the California Institute of Regenerative Medicine, and the Coulter, Culpeper,Klingenstein, Whitehall, McKnight, Yu, Woo, Snyder, and Keck Foundations.We thank the many supportive laboratories and members of the Stanfordcommunity for collaboration, advice, and equipment-sharing over this time,aswell as themanymembers of the K.D. laboratory in the Clark Center at Stan-ford over the years. O.Y. is supported by the International Human FrontierScience Program. L.E.F is supported by the Stanford MSTP program, T.J.D.is supported by the Berry Postdoctoral Fellowship, and M.M. is supportedby Bio-X, Siebel, and SGF fellowships.
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